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Stochastic adaptation and fold-change detection: from single-cell to population behavior
Tatiana T Marquez-Lago1, André Leier
1Department of Biosystems Science and Engineering, ETH Zurich, Universitätsstrasse 6, CH-8092 Zurich, Switzerland. tatiana.marquezlago@gmail.com
BMC Systems Biology
|February 5, 2011
Summary
Cellular adaptation requires sensitivity and precision. This study shows adaptation can be an emergent property of cell populations, not individual cells, highlighting the importance of probabilistic modeling.
Area of Science:
- Systems Biology
- Biophysics
- Cell Signaling
Background:
- Adaptation in cell signaling describes a system's return to equilibrium after a response.
- Perfect adaptation ensures the system returns to pre-stimulation equilibrium levels.
- Mechanisms like temperature and calcium regulation exemplify adaptation.
Purpose of the Study:
- To model the simplest adaptation architecture, a two-state protein system, in a stochastic setting.
- To analyze differences between individual and collective adaptive behaviors.
- To investigate the role of probability versus molecule numbers in adaptation.
Main Methods:
- Stochastic modeling of a two-state protein system.
- Analysis of individual versus collective cellular behavior.
- Simulations to demonstrate fold-change detection properties.
Main Results:
- Populations of cells can exhibit adaptation while individual cells do not.
- Adaptation requires understanding in terms of probability, not just molecule counts.
- The system demonstrates fold-change detection properties.
Conclusions:
- Single-cell behavior cannot always be inferred from population data.
- Adaptation can be an emergent property of collective systems.
- Ergodicity is not always applicable, even in simple linear systems, especially when molecular species mediate transitions.
